1
// rtk 的核心逻辑（伪代码）
2
use rtk::optimizer::TokenOptimizer;
3

4
fn main() {
5
    let optimizer = TokenOptimizer::new()
6
        .with_strategy("adaptive")  // 自适应压缩策略
7
        .with_min_ratio(0.6);       // 至少压缩 60%
8

9
    let tool_output = get_agent_output();
10
    let compressed = optimizer.compress(&tool_output);
11

12
    println!("原始: {} tokens", tool_output.token_count());
13
    println!("压缩后: {} tokens", compressed.token_count());
14
    println!("节省: {:.1}%", (1.0 - compressed.ratio()) * 100.0);
15
}

1
use axum::{
2
    Router,
3
    routing::get,
4
    extract::State,
5
    Json,
6
    response::IntoResponse,
7
};
8
use serde::{Serialize, Deserialize};
9
use std::sync::Arc;
10
use sqlx::PgPool;
11

12
#[derive(Serialize)]
13
struct UserResponse {
14
    id: i64,
15
    name: String,
16
    email: String,
17
    article_count: i64,
18
}
19

20
async fn get_users(
21
    State(pool): State<Arc<PgPool>>,
22
) -> impl IntoResponse {
23
    let users = sqlx::query_as!(
24
        UserResponse,
25
        r#"
26
        SELECT u.id, u.name, u.email,
27
               COUNT(a.id) as article_count
28
        FROM users u
29
        LEFT JOIN articles a ON a.author_id = u.id
30
        GROUP BY u.id
31
        ORDER BY article_count DESC
32
        LIMIT 20
33
        "#
34
    )
35
    .fetch_all(&*pool)
36
    .await
37
    .unwrap();
38

39
    Json(users)
40
}
41

42
#[tokio::main]
43
async fn main() {
44
    let pool = PgPool::connect(&std::env::var("DATABASE_URL").unwrap())
45
        .await
46
        .unwrap();
47

48
    let app = Router::new()
49
        .route("/api/users", get(get_users))
50
        .with_state(Arc::new(pool));
51

52
    let listener = tokio::net::TcpListener::bind("0.0.0.0:3000").await.unwrap();
53
    axum::serve(listener, app).await.unwrap();
54
}

1
# Polars 的使用体验（比 Pandas 快太多了）
2
import polars as pl
3

4
df = pl.read_csv("massive_dataset.csv")
5
result = (
6
    df
7
    .filter(pl.col("age") > 30)
8
    .group_by("department")
9
    .agg([
10
        pl.col("salary").mean().alias("avg_salary"),
11
        pl.col("name").count().alias("employee_count")
12
    ])
13
    .sort("avg_salary", descending=True)
14
)
15
# 处理 500 万行数据：Pandas 3.2s，Polars 0.4s

1
use ink::prelude::*
2

3
// 用 React 的方式写终端 UI
4
fn App() -> Element {
5
    let mut count = use_state(|| 0)
6

7
    rsx! {
8
        VStack {
9
            Text { size: 20, "点击计数器" }
10
            Text { "你已经点击了 {count} 次" }
11
            Button {
12
                label: "点我！",
13
                on_press: move |_| count += 1,
14
            }
15
            if count > 10 {
16
                Text { color: Color::Green, "你已经是个成熟的点击员了！" }
17
            }
18
        }
19
    }
20
}